Query Management

Query Management is the major process which helps to clean the data by system generated queries or manual queries. Queries are generated during validation checks by the sponsor or on behalf of the sponsor. These queries are then forwarded to the site that is responsible for either clarifying a detail or correcting an error. Once the query is addressed and completed, the information is resubmitted to the sponsor for entry into their database.

Traditionally, queries were created during on-site visits when clinical research associates (CRAs) or clinical trial monitors (CTMs) would painstakingly go through all of the source data, case report forms (CRFs), and other paperwork to check for consistency, completion, and any possible errors. Any discrepancies were then tracked using large spreadsheets and had to be manually checked to ensure they were resolved prior to being updated to a completed status. While it was vital for the clinical trial process, it was largely inefficient, expensive in terms of resources and time, and inconsistent because it relied heavily on the skills of the individuals doing this verification, which was not standardized between all sponsors.

Some evolutionary advancements in the process have included transferring the data directly from equipment such as blood pressure and blood sugar monitors and recruiting more than one sponsor representative to enter the data from the paper forms into a centralized database. The database software that is used is often designed to pick up inconsistencies in this data – such as an unlikely date of birth for a patient and/or values incompatible with life – and flag the discrepancies to the attention of the site staff for a manual recheck. However, due to both human and technological inaccuracy, the need for consistent verification and in person on-site visits is often still needed.

Now, with further modern-day digitization of the data management process, query management can be further simplified and used to improve the trial process. This is being done through implementing automation at several steps:

• Entry of initial data into a centralized database and digitized forms, such as eSource and eCRF.
• Targeted monitoring of data instead of verification of all data.
• Consistent use of electronic data capture systems (EDCs).
• Data transfer integration of electronic health records (EHRs) that allow for automated source checks.
• Ability to access data in near real-time without an immediate need for an on-site visit, making validation checks and monitoring for patient safety faster.
• Use of wearable devices and biosensors.
• Use of AI and data science software to check for errors, discrepancy trends in individual sites, and outliers indicating potential adverse effects.
• Automated tracking of the status of the query and resending as needed.
• Preventing cases from moving forward if there are unanswered queries.

Queries are categorized into 4 types:

Open Query:

Open Queries are those which are opened to DM or Site and not answered yet.

Example:

Answered Query:

Answered Queries are queries which are answered but not closed yet.

Example:

Closed Query:

Closed Query are queries which are closed as per the confirmation from either DM team or Site.

Cancelled Query:

Cancelled Query are queries that are cancelled by DM team due to reasons such as misfiring query, query not required, or query raised manually by mistake.

 

Next: Monitoring Visits